Applying perceptual grouping and surface models to the detection and stereo reconstruction of buildings in aerial imagery

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Abstract
In this paper, we present an approach for the detection and stereo reconstruction of buildings in aerial images using perceptual organization and surface models. First, planar models of surface are used in conjunction with radiometric information to correct a noisy and sparse disparity map obtained from an area based stereo matching. The resulting disparity map is then used by a fusion process to filter useless edges. The remaining edges are processed by a geometric grouping algorithm, which is based on perceptual organization, to detect buildings which can be modeled as a combination of rectangular structures. Finally, a new disparity map is computed for the detected buildings.

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